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Figure 1

(a) 3D simulation image of iRobt. (b) Crafted iRobt images. (c) Location of sensors, (d) Posture and parameters of the robot in two coordinate system.
(a) 3D simulation image of iRobt. (b) Crafted iRobt images. (c) Location of sensors, (d) Posture and parameters of the robot in two coordinate system.

Figure 2

Block diagram of the robot system.
Block diagram of the robot system.

Figure 3

Structure of the rotary encoder.
Structure of the rotary encoder.

Figure 4

Ultrasonic sensor.
Ultrasonic sensor.

Figure 5

Logitech BRIO 4K.
Logitech BRIO 4K.

Figure 6

(a) Magnetic sensor model and magnet reference point. (b) Calculation of position and orientation of Robot at the reference point.
(a) Magnetic sensor model and magnet reference point. (b) Calculation of position and orientation of Robot at the reference point.

Figure 7

Block diagram of a PID controller in a feedback loop.
Block diagram of a PID controller in a feedback loop.

Figure 8

(a) Voice recognition model. (b) Flowchart of the passenger answering program algorithm.
(a) Voice recognition model. (b) Flowchart of the passenger answering program algorithm.

Figure 9

The image pyramid object.
The image pyramid object.

Figure 10

(a) P-net, R-net and image processing results of NMS. (b) O-net and face detection result.
(a) P-net, R-net and image processing results of NMS. (b) O-net and face detection result.

Figure 11

Coordinates and dimensions of the bounding box in the image.
Coordinates and dimensions of the bounding box in the image.

Figure 12

Two similar triangles opposite each other.
Two similar triangles opposite each other.

Figure 13

(a) Method of determining the focal length of the camera. (b) Determine the distance using the triangle similarity method.
(a) Method of determining the focal length of the camera. (b) Determine the distance using the triangle similarity method.

Figure 14

The positional error between the robot's actual coordinates and the reference coordinates in the trajectory.
The positional error between the robot's actual coordinates and the reference coordinates in the trajectory.

Figure 15

(a) Histogram grid. (b) enlargement angle from robot to obstacle. (c) Example of blocked directions.
(a) Histogram grid. (b) enlargement angle from robot to obstacle. (c) Example of blocked directions.

Figure 16

(a) Layout diagram of ultrasonic sensors. (b) Selecting the most optimal direction among candidate direction.
(a) Layout diagram of ultrasonic sensors. (b) Selecting the most optimal direction among candidate direction.

Figure 17

Testing the model on a single sentence.
Testing the model on a single sentence.

Figure 18

Model's performance on the test set.
Model's performance on the test set.

Figure 19

(a) Passengers interact with the robot. (b) The robot leads the passenger to the check-in counter.
(a) Passengers interact with the robot. (b) The robot leads the passenger to the check-in counter.

Figure 20

(a) Airport terminal map and robot path. (b) the actual path of the robot during passenger guidance.
(a) Airport terminal map and robot path. (b) the actual path of the robot during passenger guidance.

Figure 21

Position of the reference magnets on the floor.
Position of the reference magnets on the floor.

Figure 22

Human avoidance robot process and VFH + polar histograms.
Human avoidance robot process and VFH + polar histograms.

The results of the experimental measurements of the non-calibrated program.

Number of measurements Actual distance Average prediction distance Average error Percent error average
1–10 1.2 1.19 0.01 0.83%
11–20 1.8 1.73 0.07 3.89%
21–30 2.4 2.01 0.39 16.25%

Keyword and label data sheet.

No Keywork Tag
1 Flight information, flight schedule, etc. __label__#fly_schedule#
2 Station map, etc. __label__#station_map#
3 Restaurant, cafeteria, food, food, etc. __label__#restaurant#
4 Things not to bring on board, dangerous items, etc. __label__#dangerous_object#
5 Smile, take photo, etc. __label__#capture_photo#
6 Hello, hello robot, etc. __label__#greeting#
7 bye bye, goodbye, thank you, etc. __label__#goodbye#
8 give me information about the weather, etc. __label__#weather#
9

Compare the distance measured results with the images in the laboratory environment.

Light conditions Outside light Light of the light bulb
In the practice room 50% 75%

Test result data sheet.

Researcher Number of correct classifications Number of times of misclassification Number of times unclassifiable
1 26 2 2
2 28 1 1
3 27 2 1
4 23 4 3
5 29 0 1

Results of experimental measurements of the calibrated program.

Number of measurements Actual distance Average prediction distance Average Error Percent error Average
1–10 1.2 1.18 0.02 1.67%
11–20 1.8 1.76 0.04 2.22%
21–30 2.4 2.14 0.26 2.67%

Compare the distance measured results with outdoor images.

Light conditions Harsh light Weak outdoor light Average outdoor light
Distance measurement ratio 52% 57% 90%
eISSN:
1178-5608
Langue:
Anglais
Périodicité:
Volume Open
Sujets de la revue:
Engineering, Introductions and Overviews, other